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We're looking for a DevOps / Platform Engineer to own our infrastructure end to end- both sides of it.
Side one is our multi-tenant SaaS on AWS: you build it, you run it, you keep it fast, secure, and up. Side two is the part that makes this role unusual - our enterprise customers deploy Avon AI inside their cloud (and sometimes fully air-gapped, on-prem environments). You'll own that too: packaging the platform, running the installation with the customer's infrastructure and security teams, and being the person on the call when their environment doesn't look like anyone's reference architecture.
This is a customer-facing engineering role. You'll be in rooms with enterprise IT, security, and platform teams- walking them through our architecture, answering security review questions, and unblocking deployments. If you want a pure behind-the-scenes infra job, this isn't it. If you like owning infrastructure and being the trusted technical voice in front of a customer, read on.
You'll be our first dedicated DevOps hire, which means you inherit real systems in production and a lot of room to shape how they evolve.
Key Responsibilities
EKS, networking, data stores, CI/CD, cost, and uptime. Build and evolve it with Infrastructure as Code.
Maintain and improve our Helm charts and container distribution so Avon AI installs cleanly in a customer's Kubernetes cluster.
Plan and execute installations in customers' private clouds and on-prem/air-gapped environments, working hands-on with their infrastructure teams from kickoff through go-live.
Support security reviews and architecture discussions, and translate enterprise IT constraints back into our roadmap.
IAM, network segmentation, secrets management, WAF, and the controls enterprise customers audit us on.
Metrics, logs, tracing, and alerting for our SaaS, and self-contained monitoring for customers who won't ship telemetry outside their network.
CI/CD pipelines, ephemeral PR sandboxes, release automation, and local development so engineers ship quickly and safely.
For our SaaS tenants and for deployed customer installations, including on-call ownership of what you build.

As a DevOps Engineer, you'll be a technical authority in everything cloud-native - leading feature development, making key architectural decisions, and collaborating with cross-functional teams to drive innovation.

Take an active role across all DevOps areas: our infrastructure and cloud environment, tools, services, and uptime.
Contribute to the product's architectural and infrastructure design; evaluate and implement new cloud technologies and open-source tools to improve delivery and availability of the product.
Plan and drive the growth and scale of data capacity across products.
Own the smooth, production-grade execution of delivered solutions.

We are seeking a highly experienced, AI-obsessed AI Senior Backend Engineer to join our core Engineering department. In this newly created, cross-functional role, you will be the driving force behind the companys internal AI transformation. You will act as the responsible for artificial intelligence, architecting, building, and deploying custom AI and automation systems from scratch to empower various departments and streamline operations.
Key Responsibilities
Architect, develop, and deploy tailored AI systems and applications from the ground up to solve organizational challenges.
Identify process bottlenecks across different teams and design robust backend automation solutions to optimize daily workflows.
Lead the hands-on integration of modern Generative AI models, APIs, and frameworks into the company's internal infrastructure.
Build scalable, high-performance backend microservices and APIs to support heavy data processing and AI workloads.
Act as the technical AI focal point, partnering closely with internal stakeholders and department heads to gather requirements and deliver high-impact technological solutions.
Collaborate with product, DevOps, and other teams to ensure that AI solutions are aligned with user needs and business goals.

As a Legal Counsel, you will play a key role in providing high-quality legal, regulatory, and compliance advice across multiple domains - including data protection & privacy, information security, private investment funds and employment (HR) - to all areas of the business.
You will serve as a trusted advisor to management and cross-functional teams, ensuring that our business operates within the complex global regulatory landscape while enabling innovation and growth.
We are looking for a smart, proactive, and business-oriented lawyer who is passionate about technology, people, and compliance. The ideal candidate will thrive in a fast-paced, global environment and will enjoy the challenge of navigating legal and operational issues across data, security, and HR.
Responsibilities
Provide legal support and strategic advice on a wide range of topics, including data protection, cybersecurity, HR/employment, private fund investment funds and commercial matters.
Draft, review, and negotiate various commercial agreements, including vendor, SaaS, partnership, data processing, and employment-related contracts.
Advise internal teams- including IT, Security, HR, Engineering and Finance- on compliance with applicable laws and company policies.
Ensure compliance with global privacy and data protection frameworks (GDPR, CCPA, Israeli law, etc.) and collaborate with security teams to align contractual and operational security requirements.
Contribute to the development and implementation of company-wide legal, privacy, and security governance frameworks.
Provide practical, business-focused solutions to complex legal questions in a dynamic fintech and data-driven environment.

The successful BI Team lead, will play a key role in managing and growing a team responsible for delivering impactful data products and solutions.
As a BI Team Lead, you will oversee the personal and professional development of your team, while also being the main point of contact for client-facing data initiatives. Youll drive data strategy and contribute to new initiatives that support cross-company objectives. This role involves collaborating with product managers, business stakeholders, and leadership to design, develop, and maintain scalable analytics solutions. You will also enhance the companys understanding of key business metrics by building automated tools and insightful visualizations in a rich data environment.
You will also be responsible for integrating AI and machine-learning capabilities into BI solutions, including developing automation processes and AI agents to support decision-making.

We are seeking an experienced, curious, and hands-on HR Business Partner to join our team based in TLV. In this role, you will be responsible for developing, planning, and building scalable HR processes, helping to lead change management initiatives while partnering with both leaders and employees.
You will become an expert on your teams business and collaborate with managers to develop an insightful HR strategy, effective recruiting, training, and management. You will act as a communication champion while executing HR initiatives that drive operational effectiveness and growth goals, leveraging modern HR technologies and AI tools to optimize everyday practices.
What Youll Do
Trusted advisor: Be a trusted advisor to employees and managers and support their D2D needs including coaching executive managers, team building, and employee relations.
Process Design & Optimization: Serve as a strategic advisor on organizational design, workforce planning, talent management, and team effectiveness. Design, build, and optimize structured HR processes, using people data and metrics to shape and refine these processes.
Data-Informed Decision Making: Utilize People Analytics and key HR metrics to gain insights, identify trends, and proactively address matters of engagement, retention, and organizational health.
AI & HR Efficiencies: Explore and integrate AI-driven tools and automation into daily HR workflows (such as content creation, talent mapping, and process optimization) to enhance team productivity.
Talent Management: Lead talent processes including performance management, succession planning, and career development. Be a design partner to optimize hiring funnels, ensuring recruitment processes align with business growth goals and a holistic talent management strategy.
COE Collaboration: Collaborate with HR centers of excellence (Talent Acquisition, Compensation, etc.) to deliver integrated people solutions.
Employee Relations: Support employee relations efforts by providing guidance on policy, performance concerns, and conflict resolution.
Change Management: Champion change management initiatives to ensure smooth adoption of new processes, systems, and organizational changes.
Project management: Support and execute various projects within the HR domain.
Continuous Improvement: Continuously optimize the way we do things!

What You Will Be Doing
Lead and grow a high-performing engineering organization responsible for our core product offering.
Define and execute the engineering strategy for our Kubernetes resource management platform, enabling DevOps teams worldwide to operate more efficiently.
Partner closely with Product, Design, and Go-to-Market leaders to translate business strategy into engineering execution.
Drive technical excellence, architectural direction, and engineering best practices across multiple teams.
Build, mentor, and develop engineering managers and senior engineers, fostering a culture of ownership, innovation, and continuous improvement.
Scale engineering processes, organizational structure, and delivery capabilities while maintaining a high bar for quality and execution.
Balance hands-on technical leadership with organizational leadership, making key architectural and strategic decisions when needed.
Create an environment where talented engineers can do their best work with a high degree of autonomy, accountability, and collaboration.

We are looking for a Lead Data Scientist to lead strategic research initiatives. This individual will be at the forefront of our companys research, working hands-on to advance our models while also mentoring and collaborating with data scientists across the department.
Responsibilities
Spearhead strategic research of new cutting edge Machine Learning models
Mentor and advise data scientists in the Auto loans research team as well as across the research department
Design solutions for the companys core mission using Data Science methodologies from various domains
Work in a short life-cycle research and development environment
Generate and test working hypotheses in unexplored territory.

We're forming a new AI Group and looking for a Senior AI Engineer to help shape it from an early stage - a greenfield, long-term effort to evolve how decisions are made across our platform using AI-driven systems. You won't just integrate APIs or build demos; you'll build the AI brain that works alongside (and increasingly drives) our core automation engine, with real production impact from day one and room to grow into technical leadership as the group scales.

Agentic AI Architecture: Design and build autonomous AI agents that analyze infrastructure in real time and make intelligent decisions. Work with modern agentic frameworks (LangGraph, PydanticAI) and conversational AI to create multi-agent systems - including troubleshooting, optimization, FinOps, and how-to agents. Leverage core LLM capabilities (tool-use, memory, retrieval) to operate safely in production.
Platform Integration & Intelligent Decision Systems: Develop MCPs to expose our capabilities to AI agents that reason over infrastructure environments, metrics, configurations, and cost signals. Build integrations with tools like Slack, Jira, and AI-powered IDEs (Cursor, Windsurf) to deliver context-aware insights, from "why is this pod not scheduling?" to "how can we reduce costs by 30% safely?"
AI Model Development & MLOps: Build and deploy machine learning models that learn from infrastructure patterns - detecting the right resource policies for workloads, predicting optimal scaling triggers, and recommending GPU configurations. Own the complete ML pipeline from training to production, ensuring models are reliable, monitored, and continuously improving.
R&D AI Tools Development & Adoption: Build and embed internal AI tools to accelerate engineering, development, research, and support.
AI Tools for Business Impact: Develop AI-powered tools that help Sales and Support teams demonstrate value instantly - agents that analyze customer infrastructure, generate cost optimization reports automatically, and turn technical data into clear business recommendations.
End-to-End Ownership: Own AI systems from concept to production, ensuring they're fast (sub-2-second responses), reliable, safe, and cost-effective. Build evaluation frameworks to measure quality, implement security controls, and balance performance tradeoffs in production.
Technical Leadership: Define AI architecture and best practices as a founding member of the AI team. Make key technical decisions - choosing frameworks, designing multi-agent systems, establishing data governance - and shape how we evolve from AI-enhanced internal tools to customer-facing AI products.